ocr_utils.py 文件源码

def read_and_decode(filename_queue):
  reader = tf.TFRecordReader()
  _, serialized_example = reader.read(filename_queue)
  features = tf.parse_single_example(
      serialized_example,
      features={
          'height': tf.FixedLenFeature([], tf.int64),
          'width': tf.FixedLenFeature([], tf.int64),
          'image_raw': tf.FixedLenFeature([], tf.string),
          'label': tf.VarLenFeature(tf.int64),
      })

  image = tf.decode_raw(features['image_raw'], tf.uint8)
  image = tf.reshape(image, [730, 38])

  image = tf.cast(image, tf.float32) * (1. / 255) - 0.5

  label = tf.cast(features['label'], tf.int32)

  return image, label